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Proceedings Paper

Application of minimum error neural network (MENN) method to target recognition
Author(s): Weiping Yang; Zhenkang Shen; Zhiyong Li; Hai-Xin Shen
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Paper Abstract

In this paper, we introduce a neural network recognition method, MENN (minimum error neural network) method, in target recognition. From the target gray sequences, we can extract some useful characteristics. Then we use these features as the input data of the MENN classifier. By these characteristics, using the MENN classifier we can easily pick out the true targets from the candidate target sequences. MENN recognition method can not only pick out the true target and reject the false targets, but it also gets rid of the baits. Therefore, it has high reliability. Moreover, it has many advantages, for example, its training is a one pass process, its test process is not only simple but also straightforward, and its calculation is simple, etc. On account of those advantages, MENN recognition method is adaptive to the need of realtime processing.

Paper Details

Date Published: 21 September 1994
PDF: 10 pages
Proc. SPIE 2298, Applications of Digital Image Processing XVII, (21 September 1994); doi: 10.1117/12.186594
Show Author Affiliations
Weiping Yang, National Univ. of Defense Technology (China)
Zhenkang Shen, National Univ. of Defense Technology (China)
Zhiyong Li, National Univ. of Defense Technology (China)
Hai-Xin Shen, National Univ. of Defense Technology (China)

Published in SPIE Proceedings Vol. 2298:
Applications of Digital Image Processing XVII
Andrew G. Tescher, Editor(s)

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